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Patent Search

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RobThePCGuy
patent-search

Search 100M+ patents via the MCP server's BigQuery tools. No standalone scripts; everything goes through the MCP tools registered by the patent-creator server.

Overview

PublisherRobThePCGuy
RepositoryClaude-Patent-Creator
Skill namepatent-search
Stars
203
Forks
33
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by RobThePCGuy on GitHub. Read the source before you install it.

Installation

Install the Patent Search AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/RobThePCGuy/Claude-Patent-Creator/tree/main/skills/patent-search
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/RobThePCGuy/Claude-Patent-Creator.git /tmp/Claude-Patent-Creator
mkdir -p .claude/skills
cp -r /tmp/Claude-Patent-Creator/skills/patent-search .claude/skills/patent-search
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Patent Search in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Patent Search on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Patent Search is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Patent Search Skill

This skill points Claude at the BigQuery patent-search tools registered by the patent-creator MCP server. Call the tools directly; do not shell out to Python.

When to use

  • Find prior art by keyword, classification, or family.
  • Pull full patent records (title, abstract, claims, description) for US patents.
  • Cross-reference an EP/WO patent into its US family member to get full text.

Available MCP tools

ToolWhat it does
search_patents_googleRecommended. Full-text keyword search worldwide (claims and description included), one search credit per call. Needs SERPAPI_API_KEY (free plan: 250/month).
check_google_patents_statusIs the key set, and how many searches are left this month (free to call).
search_patents_bigqueryFallback keyword search across title / abstract / claims (US only for claims). ~341 GiB, about $2, per search.
get_patent_bigqueryPatent details by publication number: bibliographic data + claims by default; abstract and description are opt-in.
get_patents_bigquerySame, for up to 50 patents in one query at the cost of one lookup.
search_patents_by_cpc_bigquerySearch by CPC classification prefix.
search_patents_by_ipc_bigquerySearch by IPC classification prefix (good for older or non-US patents).
search_patent_family_bigqueryAll publications sharing a family ID across jurisdictions.
check_bigquery_statusVerify auth and quota project before a long workflow.

Cost notes

BigQuery on-demand pricing is $6.25 / TiB (1 TiB free per month). The MCP server enforces a per-query bytes-billed ceiling, defaulting to 350 GiB. Override via PATENT_BIGQUERY_MAX_BYTES_BILLED if you need a larger scan window.

The patents table is unclustered, so a detail lookup costs the same for one patent or fifty; the cost depends only on which sections are requested:

Detail lookupScanCost
Bibliographic only (include_claims=False): title, dates, family_id, CPC/IPC~44 GiB~$0.27
Default: + claims~160 GiB~$1
+ abstract (include_abstract=True)+~200 GiBexceeds the default cap together with claims
+ description (include_description=True)~1.1 TiBexceeds the default cap

So: batch with get_patents_bigquery, pass include_claims=False when you only need codes or family_id, and take abstracts from the search results rather than re-fetching them.

Choosing keywords

search_patents_google:

  • All words must match; "double quotes" match an exact phrase. No stemming, so search synonyms and plurals separately.
  • Lead with the invention's distinctive terms. Common words match thousands of patents and push the closest art down; in testing, adding "heart valve" to a query buried the target past #300, while its distinctive claim words found it at #48.
  • Use limit=100: it costs the same one credit as limit=10.
  • Stay inside a classification by adding a full CPC group: "voice biometric" CPC=G10L17/00 (a bare CPC=G10L17 finds nothing).
  • Results show one row per publication, so a US patent and its EP family member can both appear.

search_patents_bigquery (fallback):

  • 2-3 keywords work better than long phrases (BigQuery LIKE matching is literal).
  • For non-US patents, claims is empty in the dataset; the MCP keyword tool already searches title/abstract for those jurisdictions. For full text on EP/WO, use the EPO OPS tools instead.
  • Use search_patent_family_bigquery to bridge from an EP/WO hit to its US family member when you need claims.

Common workflows

Prior art sweep:

  1. search_patents_google(query=…, limit=100) — broad full-text scan, worldwide (fallback: search_patents_bigquery(query=…, country="US")).
  2. Pick the top hits' CPC codes with one get_patents_bigquery(patent_numbers=[…], include_claims=False).
  3. search_patents_google(query="<terms> CPC=<group>/00", limit=100) — pull adjacent technology (fallback: search_patents_by_cpc_bigquery, ~234 GiB a search).

Cross-jurisdiction lookup:

  1. search_patents_google(query=…, country="EP") (fallback: search_patents_bigquery(query=…, country="EP")).
  2. For the EP hits, one get_patents_bigquery(patent_numbers=[…], include_claims=False) to get their family_ids.
  3. search_patent_family_bigquery(family_id=…) to find the US member with full claims.

Frequently asked questions

What does the Patent Search AI skill do?

Search 100M+ patents via the MCP server's BigQuery tools. No standalone scripts; everything goes through the MCP tools registered by the patent-creator server.

Why use Patent Search on TypingMind?

Because you install it once and use it with any model. Patent Search is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Patent Search in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/RobThePCGuy/Claude-Patent-Creator/tree/main/skills/patent-search. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Patent Search?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Patent Search?

As many as you like. As long as a model supports skills, you can use Patent Search with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Patent Search AI skill free?

Yes. It is published on GitHub by RobThePCGuy under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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